class_docstr: Simple online and realtime tracking with a deep association metric.
  
  Details can be found at `DeepSORT<https://arxiv.org/abs/1703.07402>`_.
  
  Args:
      detector (dict): Configuration of detector. Defaults to None.
      reid (dict): Configuration of reid. Defaults to None
      tracker (dict): Configuration of tracker. Defaults to None.
      data_preprocessor (dict or ConfigDict, optional): The pre-process
         config of :class:`TrackDataPreprocessor`.  it usually includes,
          ``pad_size_divisor``, ``pad_value``, ``mean`` and ``std``.
      init_cfg (dict or list[dict]): Configuration of initialization.
          Defaults to None.
code: def __init__(
      self,
      detector: Optional[dict] = None,
      reid: Optional[dict] = None,
      tracker: Optional[dict] = None,
      data_preprocessor: OptConfigType = None,
      init_cfg: OptConfigType = None,
  ):
      super().__init__(data_preprocessor, init_cfg)
  
      if detector is not None:
          self.detector = MODELS.build(detector)
  
      if reid is not None:
          self.reid = MODELS.build(reid)
  
      if tracker is not None:
          self.tracker = MODELS.build(tracker)
  
      self.preprocess_cfg = data_preprocessor
  
file_path: mmdetection/mmdet/models/mot/deep_sort.py
imports: from typing import Optional
  from torch import Tensor
  from mmdet.registry import MODELS
  from mmdet.structures import TrackSampleList
  from mmdet.utils import OptConfigType
  from .base import BaseMOTModel
label_desc: Use image node_id 1 to create a new DeepSORT object from inherited base classes: BaseMOTModel with example: obj = DeepSORT(detector, reid, tracker, data_preprocessor, init_cfg)